재활환자 모의보행 패턴분석을 이용한 하지 편측 장애자의 정량적 재활상태 모니터링
Quantitative Rehabilitation Extent Monitoring for Unilateral Lower Extremity Disabled Patients using Simulated Gait Pattern Analysis
0
조회
0
다운로드
0
인용
0
참고문헌
키워드
초록
In this paper, to quantitatively evaluate the degree of rehabilitation for the disabled of unilateral lowerextremity, we compared the EMG pattern of normal and simulated abnormal gait. The EMG signal was measuredat a rate of 1 kHz on the quadriceps and biceps femoris, the pressure sensor was attached to the sole in order todistinguish the gait cycle. Integrated EMG (IEMG) was obtained by the gait cycle, and classified four patterns thatwere the normal gait pattern, amplitude decrease pattern, reversed pattern, and irregular pattern. For comparisonof the patterns, a curve fitting was performed using the trigonometric functions. The result of curve fitting, themethod using a variable A that corresponds to the amplitude of the regression curve was able to distinguish thereverse pattern and remaining pattern. The coefficient of determination (R2) representing coincidence of the patternof the regression curve and EMG was confirmed the biggest value at the normal gait. Therefore, the degree of normalgait can be confirmed using the coefficient of determination. This results show that it is possible to quantitativelyconfirm the degree of unilateral lower extremity disabled rehabilitation, and it will be contributed to the study of efficientrehabilitation methods by objective analysis.
Abstract
In this paper, to quantitatively evaluate the degree of rehabilitation for the disabled of unilateral lowerextremity, we compared the EMG pattern of normal and simulated abnormal gait. The EMG signal was measuredat a rate of 1 kHz on the quadriceps and biceps femoris, the pressure sensor was attached to the sole in order todistinguish the gait cycle. Integrated EMG (IEMG) was obtained by the gait cycle, and classified four patterns thatwere the normal gait pattern, amplitude decrease pattern, reversed pattern, and irregular pattern. For comparisonof the patterns, a curve fitting was performed using the trigonometric functions. The result of curve fitting, themethod using a variable A that corresponds to the amplitude of the regression curve was able to distinguish thereverse pattern and remaining pattern. The coefficient of determination (R2) representing coincidence of the patternof the regression curve and EMG was confirmed the biggest value at the normal gait. Therefore, the degree of normalgait can be confirmed using the coefficient of determination. This results show that it is possible to quantitativelyconfirm the degree of unilateral lower extremity disabled rehabilitation, and it will be contributed to the study of efficientrehabilitation methods by objective analysis.
참고문헌 (15)
- J. Perry, "Gait analysis 2nd ed", pp.3~164 (2010), SLACK. INC
- 이성원, "관절염의 신체 검사", 대한내과학회지, 83(2), pp.162~173 (2012), 대한내과학회[DOI]
- 유향미, "3축 가속도 센서를 이용한 보행 횟수 검출 알고리즘과 활동 모니터링", 한국콘텐츠학회 논문지, 8(8), pp.253~260 (2008), 한국콘텐츠학회
- 장은혜, "근전도와 저항 센서를 이용한 보행 단계 감지", 감성과학, 13(1), pp.207~214 (2010), 한국감성과학회
- Hyo-Ki Lee., "The Study of Gait Analysis for Hemiplegic Patient Using 3-axis Acceleration Signal", IEEK summer conference, pp.869~870 (2006)
- A. L. Hof., "Detection of non-standard EMG profiles in walking", Gait Posture, 21, pp.171~177 (2005)
- E. Ueno., "Gait disorders in parkinsonism : a study with floor reaction forces and EMG", Advances in neurology, 60, pp.414~418 (1993)
- E. Isakov., "Trans-tibial amputee gait : Time-distance parameters and EMG activity", Prosthetics and Orthotics International, 24, pp.216~220 (2000)
- D. C. Kerrigan., "Can toewalking contribute to stiff-legged gait?", American Journal of Physical Medicine & Rehabilitation, 80(1), pp.33~37 (2001)
- F. E. Zajac., "Biomechanics and muscle coordination of human walking : part II : lessons from dynamical simulations and clinical implications", Gait & Posture, 17(1), pp.1~17 (2003)
- 김택훈, "정상인에서 쭈그림보행 시뮬레이션 시 관찰된 보상적 전략", 한국전문물리치료학회지, 11(1), pp.53~67 (2004), 한국전문물리치료학회
- Scott M. Colby., "Electromyographic analysis and energy expenditure of harness supported treadmill walking : implications for knee rehabilitation", Gait and Posture, 10, pp.200~205 (1999)
- Nick D. Panagiotacopulos, "Evaluation of EMG signals from rehabilitated patients with lower back pain using wavelets", Journal of Electromyography and Kinesiology, 8, pp.269~278 (1998)
- C. Larivie`re, "Evaluation of measurement strategies to increase the reliability of EMG indices to assess back muscle fatigue and recovery", Journal of Electromyography and Kinesiology, 12, pp.91~102 (2002)
- 이영진, "sEMG 분석을 이용한 높이 들어올리기 자세에서의 신체적 작업부하의 정량적 평가방법 개발", 의공학회지, 32(4), pp.328~335 (2011), 대한의용생체공학회